Day 6 - Longest Consecutive Subsequence.md

Difficulty	Source	Tags
Medium	160 Days of Problem Solving	Hash

🚀 Day 6. Longest Consecutive Subsequence 🧠

The problem can be found at the following link: Problem Link

💡 Problem Description:

Given an array arr[] of non-negative integers, find the length of the longest subsequence such that the elements in the subsequence are consecutive integers. The consecutive numbers can be in any order.

🔍 Example Walkthrough:

Input:
arr[] = [2, 6, 1, 9, 4, 5, 3]
Output:
6
Explanation:
The consecutive numbers are [1, 2, 3, 4, 5, 6]. These 6 numbers form the longest consecutive subsequence.

Input:
arr[] = [1, 9, 3, 10, 4, 20, 2]
Output:
4
Explanation:
The consecutive numbers are [1, 2, 3, 4]. These 4 numbers form the longest consecutive subsequence.

Input:
arr[] = [15, 13, 12, 14, 11, 10, 9]
Output:
7
Explanation:
The consecutive numbers are [9, 10, 11, 12, 13, 14, 15]. These 7 numbers form the longest consecutive subsequence.

Constraints:

• $1 <= arr.size() <= 10^5$
• $0 <= arr[i] <= 10^5$

🎯 My Approach:

1. Set-based Consecutive Detection:
   The core idea is to leverage a hash set for fast lookups.

   • Insert all elements of the array into a set.
   • For each number in the set, check if it is the starting number of a sequence (i.e., num - 1 is not in the set).
   • If it is a starting number, count how many consecutive numbers exist in the sequence.
   • Keep track of the maximum sequence length.

2. Steps:

   • Add all elements of the array to a hash set.
   • Traverse each number in the set.
   • If a number is the start of a sequence, calculate the length of the sequence.
   • Update the maximum sequence length as required.

🕒 Time and Auxiliary Space Complexity

• Expected Time Complexity: O(n), as we traverse the array and perform O(1) operations for each element using a hash set.
• Expected Auxiliary Space Complexity: O(n), as the hash set requires additional space to store all elements of the array.

📝 Solution Code

Code (C++)

class Solution {
public:
    int longestConsecutive(vector<int>& nums) {
        unordered_set<int> numSet(nums.begin(), nums.end());
        int longest = 0;

        for (int num : numSet) {
            if (!numSet.count(num - 1)) {
                int current = num, count = 1;
                while (numSet.count(current + 1)) current++, count++;
                longest = max(longest, count);
            }
        }
        return longest;
    }
};

👨‍💻 Alternative Approach

Alternative Using Sorting

1. Sort the array and traverse to find consecutive elements.
2. Time Complexity: O(n log n) due to sorting.
3. Auxiliary Space Complexity: O(1) if sorting in place.

Code:

class Solution {
public:
    int longestConsecutive(vector<int>& nums) {
        if (nums.empty()) return 0;
        sort(nums.begin(), nums.end());
        int longest = 1; 
        int count = 1;   
        for (int i = 1; i < nums.size(); i++) {
            if (nums[i] == nums[i - 1]) continue;
            if (nums[i] == nums[i - 1] + 1) {
                count++; 
            } else {
                longest = max(longest, count);
                count = 1;
            }
        }
        return max(longest, count);
    }
};

Code (Java)

class Solution {
    public int longestConsecutive(int[] nums) {
        HashSet<Integer> numSet = new HashSet<>();
        for (int num : nums) numSet.add(num);

        int longest = 0;
        for (int num : numSet)
            if (!numSet.contains(num - 1)) {
                int count = 1;
                while (numSet.contains(++num)) count++;
                longest = Math.max(longest, count);
            }
        return longest;
    }
}

Code (Python)

class Solution:
    def longestConsecutive(self, arr):
        num_set = set(arr)
        longest = 0

        for num in num_set:
            if num - 1 not in num_set:
                current, count = num, 1
                while current + 1 in num_set:
                    current += 1
                    count += 1
                longest = max(longest, count)

        return longest

🎯 Contribution and Support:

For discussions, questions, or doubts related to this solution, feel free to connect on LinkedIn: Any Questions. Let’s make this learning journey more collaborative!

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